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Continuous Time Model Estimation

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Abstract

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the trend model by simulation, and how to calculate standard errors from estimation of the noise model. It also discusses the numerical difficulties involved in discrete time models that bring about the unit roots illusion in econometrics.

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File URL: http://www.finance.uts.edu.au/research/wpapers/wp138.pdf
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Bibliographic Info

Paper provided by Finance Discipline Group, UTS Business School, University of Technology, Sydney in its series Working Paper Series with number 138.

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Date of creation: 01 Dec 2004
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Handle: RePEc:uts:wpaper:138

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Keywords: Continuous time model; Estimation; Trend and noise decomposition; Unit roots illusion;

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  1. Carl Chiarella & S. Gao, 2002. "Modelling the Value of the S&P 500 - A System Dynamics Perspective," Working Paper Series 115, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  2. Chiarella, Carl & Gao, Shenhuai, 2004. "The value of the S&P 500--A macro view of the stock market adjustment process," Global Finance Journal, Elsevier, vol. 15(2), pages 171-196, August.
  3. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
  4. Carl Chiarella & S. Gao, 2002. "Type I Spurious Regression in Econometrics," Working Paper Series 114, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
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Cited by:
  1. Carl Chiarella & S. Gao, 2002. "Modelling the Value of the S&P 500 - A System Dynamics Perspective," Working Paper Series 115, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  2. Chiarella, Carl & Gao, Shenhuai, 2004. "The value of the S&P 500--A macro view of the stock market adjustment process," Global Finance Journal, Elsevier, vol. 15(2), pages 171-196, August.

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